AI training needs production telemetry
1,720 Wall Street employees, 53 workshops, one uncomfortable number — 3-5% of power users generate over 70% of usage. Workshops without telemetry don't spread capability; they concentrate it in people who already had it.
GAI Insights published seven months of data from running AI workshops inside financial services: 1,720 employees, 53 sessions across 8 firms, one-to-four-hour formats at introductory and intermediate levels. First-party consultancy data, unaudited, with obvious selection bias — the firms that buy workshops are not a random sample — so hold the exact figures loosely. I will anyway, because one of them matches everything I have seen from the inside of enterprise AI programs:
3% to 5% of power users generated more than 70% of the usage.
Sit with what that distribution means for the workshop model. You train a thousand seats. You report a thousand seats trained. And then the actual work — the measurable pull on the tools — comes from thirty or forty people, most of whom, in my experience, were already the ones experimenting before the training budget existed. The detail from the same dataset that seals it: most employees who described themselves as daily AI users had never set up custom instructions, projects, or reusable skills. Self-reported fluency, structurally shallow usage.
A workshop without follow-through doesn't spread capability across an organization. It concentrates value in the people who already had the disposition — and issues everyone else a certificate of awareness.
Why the workshop model produces this curve
Nothing is wrong with the workshops themselves. Awareness is real and necessary: people cannot adopt what they cannot imagine. The failure is treating awareness as the deliverable, when three harder problems remain untouched the moment the session ends.
Workflow design. "Use AI" is not a workflow. The analyst who leaves the session inspired still returns to a desk where the actual task — the Monday report, the client memo — has no designed AI-shaped path through it. Power users invent their own paths; that is what makes them power users. Everyone else needs the path drawn, for their specific work, with their firm's approved tools.
Manager reinforcement. Usage survives where a manager expects it, asks about it, and treats it as how work is done — the same finding, incidentally, that GAI reports at firm level: adoption tracks how much leadership itself uses the tools daily. A workshop the manager didn't attend produces a behavior the manager doesn't reinforce, and unreinforced behavior decays in weeks.
Safe practice. In a regulated firm, the median non-user is not lazy — they are unsure what they are allowed to paste, and the safest interpretation of ambiguity is abstinence. No amount of inspiration fixes a permission question. Only explicit, work-specific guardrails do.
The operating loop that replaces the calendar
The alternative is to run fluency the way you run production software — instrumented, iterated, coached:
rendering diagram…
The load-bearing box is the first one. Without telemetry, a transformation lead can count trained seats but cannot answer the three questions that matter: which workflows actually changed, who stopped using the tools after week two, and where an hour of coaching would move a whole team. With telemetry, the 70/5 curve stops being a verdict and becomes a work list — every team stuck at zero is a coaching target, every power user is a source of playbooks worth harvesting, every drop-off is a signal that a workflow or a permission is broken.
At work I sat with a transformation lead this year whose dashboard was, in its entirety, seats trained and a satisfaction score — 4.6 out of 5, genuinely. When we pulled actual usage from the platform logs, two-thirds of trained users had not touched the tools in the thirty days after their session, and the distribution among the rest was exactly the shape GAI describes. Nobody had lied. The program was simply measuring attendance at the theatre and calling it fitness. The uncomfortable meeting where the real curve went on the wall was also the most productive one of the engagement: the budget moved from more workshops to telemetry, team-level coaching, and a library of harvested power-user workflows — the same money, pointed at the gap instead of the calendar.
My rule for enablement budgets now: no telemetry, no training spend. Instrument first, even crudely — platform logs and a monthly pull are enough to start. Awareness sessions are the cheapest part of the program and the only part most programs fund. The expensive parts — workflow design per team, manager enablement, guardrail clarity — are exactly the parts that never fit in a hall of two hundred people, which is why they get skipped, which is why the curve stays at 70/5.
Steal this
Three numbers on one page, monthly, per team: active users in the last 30 days (from logs, not surveys), the usage share of the top 5% (your concentration index), and workflows-changed (count only cases where a recurring deliverable is now produced differently — named, verifiable). If the concentration index isn't falling quarter over quarter, you are not running an adoption program. You are running a fan club for your power users — and paying workshop rates for the privilege.
Seats trained is theatre attendance; telemetry is fitness — instrument the gym before you book more seminars.
